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Environmental(Friendly)SupercomputingonSuperMUC
DieterKranzlmüller
Munich NetworkManagementTeamLudwig-Maximilians-UniversitätMünchen(LMU)&LeibnizSupercomputing Centre (LRZ)of the Bavarian Academy of Sciences and Humanities
FlashFlood Genoa,Italy, 2011
D.Kranzlmüller Cracow,26October2016 2
http://www.drihm.eu/images/video/DRIHM_final.mp4
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FlashFloods
n Formswiftlydueto(extremely)highrainfallrates
n Littleornopriorwarning
n Devastatingconsequences(casualties,economiclosses,...)
D.Kranzlmüller Cracow,26October2016 3
UNISDR– TheUnitedNationsOfficeforDisasterRiskReduction
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https://www.unisdr.org/
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GAR– GlobalAssessmentReportonDisasterRiskReduktion 2015
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http://www.preventionweb.net/english/hyogo/gar/2015/en/home/GAR_2015/GAR_2015_6.html
NumberofDisastersperRegion
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http://www.emdat.be/disaster_trends/index.html
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MunichRe– LossEventsWorldwide2014
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http://www.preventionweb.net/files/41773_munichreworldmapnaturalcatastrophes.pdf
FlashFloods
n Formswiftlydueto(extremely)highrainfallrates
n Littleornopriorwarning
n Devastatingconsequences(casualties,economiclosses,...)
n Monitoringandforecastingoffloods:– EuropeanFloodAwarenessSystem(EFAS)– GlobalFloodDetectionSystem(GFDS)– GlobalFloodAwarenessSystem(GloFAS)
n Problem:spatialresolution50-100kmè Flashfloodsremainundetected
D.Kranzlmüller Cracow,26October2016 8
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TheEUProjectSeriesDRIHM*
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PossibleSolution– EnvironmentalComputing
n Combinemeteorology,hydrology,hydraulicsthroughcomputerscience
n Increasespatialandtemporalresolution(dataquality)– RegionalClimateModels(RCM)
n Computeensemblesofforecaststocoverallpotentialoutcomes
n Startandfinishcomputationintimetoprovideleadtimeforevacuationmeasures
è Simulateensemblesofforecastswithhigh-resolutionon
high-performancecomputing(HPC)infrastructuresondemandwhentriggeredbyincreasedrainfallrates
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Notinthis talk
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LeibnizSupercomputingCentreoftheBavarianAcademyofSciencesandHumanities
D.Kranzlmüller Cracow,26October2016 11
Withapprox.230employeesformorethan100.000studentsandformorethan30.000employeesincluding8.500scientists
• EuropeanSupercomputingCentre• National SupercomputingCentre
• RegionalComputerCentreforallBavarianUniversities• ComputerCentreforallMunichUniversities
Photo:ErnstGraf
LeibnizSupercomputingCentreoftheBavarianAcademyofSciencesandHumanities
n EuropeanSupercomputingCentre
n NationalSupercomputingCentre
n RegionalComputerCentreforallBavarianUniversities
n ComputerCentreforallMunichUniversities
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SGI UV
SGI Altix
Linux Clusters
SuperMUC
Linux Hosting and Housing
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SuperMUC@LRZ
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Video: SuperMUC rendered on SuperMUC by LRZ
http://youtu.be/OlAS6iiqWrQ
Top500SupercomputerList(June2012)
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www.top500.org
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LRZSupercomputers
D.Kranzlmüller 15
SuperMUC PhaseII
Cracow,26October2016
SuperMUC Phase 1 + 2
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SuperMUC System@LRZ
Phase2(LenovoNeXtScale WCT):
• 3.6PFlops peakperformance• 3072LenovoNeXtScale nx360M5WCT
nodesin6computenodeislands• 2IntelXeonE5-2697v3processorsand64
GBofmemorypercomputenode• 86,016computecores• NetworkInfiniband FDR14(fattree)
CommonGPFSfilesystemswith10PBand5PBusablestoragesizerespectivelyCommonprogrammingenvironment
Directwarm-watercooledsystemtechnology
Phase1(IBMSystemxiDataPlex):
• 3.2PFlops peakperformance• 9216IBMiDataPlex dx360M4nodesin18
computenodeislands• 2IntelXeonE5-2680processorsand32
GBofmemorypercomputenode• 147,456computecores• NetworkInfiniband FDR10(fattree)
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PowerConsumptionatLRZ
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0
5.000
10.000
15.000
20.000
25.000
30.000
35.000
Stro
mve
rbra
uch
in M
Wh
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CoolingSuperMUC
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SuperMUCPhase2@LRZ
Cracow,26October2016
HighEnergyEfficiencyü UsageofIntelXeonE52697v3processorsü Directliquidcooling
- 10%poweradvantageoveraircooledsystem- 25%poweradvantageduetochiller-lesscooling
Photos:TorstenBloth,Lenovo
ü Energy-aware scheduling- 6%poweradvantage- ~40%poweradvantage- Totalannualsavingsof~2Mio.€
forSuperMUCPhase1and2D.Kranzlmüller 20Slide:HerbertHuber
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LRZ Application Mix
n Computational Fluid Dynamics: Optimisation of turbines andwings, noise reduction, air conditioning in trains
n Fusion: Plasma in a future fusion reactor (ITER)n Astrophysics: Origin and evolution of stars and galaxiesn Solid State Physics: Superconductivity, surface propertiesn Geophysics: Earth quake scenariosn Material Science: Semiconductorsn Chemistry: Catalytic reactionsn Medicine and Medical Engineering: Blood flow, aneurysms, air
conditioning of operating theatresn Biophysics: Properties of viruses, genome analysisn Climate research: Currents in oceans
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Results (Sustained TFlop/s on 128000 cores)
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Name MPI #cores Description TFlop/s/island TFlop/smaxLinpack IBM 128000 TOP500 161 2560Vertex IBM 128000 PlasmaPhysics 15 245GROMACS IBM,Intel 64000 MolecularModelling 40 110Seissol IBM 64000 Geophysics 31 95waLBerla IBM 128000 LatticeBoltzmann 5.6 90LAMMPS IBM 128000 MolecularModelling 5.6 90APES IBM 64000 CFD 6 47BQCD Intel 128000 QuantumPhysics 10 27
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PartnershipInitiativeComputationalSciencesπCS
n Individualizedservicesforselectedscientificgroups– flagshiprole– Dedicatedpoint-of-contact– Individualsupportandguidanceandtargetedtraining &education– PlanningdependabilityforusecasespecificoptimizedITinfrastructures– EarlyaccesstolatestITinfrastructure(hard- andsoftware)developments
andspecificationoffuturerequirements– AccesstoITcompetencenetworkandexpertiseatCSandMath
departmentsn Partnercontribution
– EmbeddingITexpertsinusergroups– Jointresearchprojects(includingfunding)– Scientificpartnership– equalfooting– jointpublications
n LRZbenefits– Understandingthe(currentandfuture)needsandrequirementsofthe
respectivescientificdomain– Developingfutureservicesforallusergroups– Thematicfocusing:EnvironmentalComputing
D. Kranzlmüller Cracow,26October2016 23
SeisSol - Numerical Simulationof Seismic WavePhenomena
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Picture:AlexBreuer(TUM)/ChristianPelties(LMU)
Dr.ChristianPelties,Departmentof Earthand EnvironmentalSciences (LMU)Prof.MichaelBader,Departmentof Informatics (TUM)
1,42Petaflop/son147.456Coresof SuperMUC(44,5%of PeakPerformance)
http://www.uni-muenchen.de/informationen_fuer/presse/presseinformationen/2014/pelties_seisol.html
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Conclusions
n EnvironmentalComputingneedsIT-Infrastructures(includingHPC)
n EnergyEfficiency isanimportantparttomaximizescientificthroughput
n Computationalscienceneedstobeanintegralpartofteachingdomainscientists– LearnhowtogetaccesstoHPCinfrastructures– LearnhowtoprogramHPCinfrastructureswithincreasingcomplexity,
heterogeneityandscalability– efficiency,reliability,portabiliy
n TheLRZPartnershipInitiativeComputationalScience(piCS)triestoimproveusersupport
http://www.sciencedirect.com/science/article/pii/S1877050914003433
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TheEUCopernicusEarthObservationPlatform
n TheCopernicusSentinel Missions are „game changers“for EarthObservation:watch the heartbeat of the planet
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Sentinel 2Sentinel 1
10m,every 2daysca.3PByte permonth
raw data
10m,every 2..5daysca.4.5PByte permonth
raw data
SlidecourtesyWolframMauser
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Complex ImageAnalysisderivesEnvironmentalParameters
n Example:quantitativesatellite image analysis of wheat fields
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Chlorophyllcontent [µg/m²]Satellite image
Parameters,e.g.:Plantspecies,biomass,chlorophyll,pests,phenology,…
SlidecourtesyWolframMauser
EnvironmentalComputing
n Human-Environment-Relation- ObservationsandSimulationsforalternativeGlobalFutures
n Massivecomputingresourcesareneededtocreateacyber-environmentalsystem inwhichtherealandthevirtualworldcaninteract:– toturnremotesensingimagedatastreamsintomeaningfulenvironmental
informationforeachfarmerontheglobe– toidentifyleastinvasivewaysforagriculture– todoublefoodproductionandshowthe
globalenvironmentalbenefitsithas– tosimulateandassessthetotal
environmentandthehumaninterventionsbeforetheyoccur
– toexplorealternativefutureenvironmentsandtheirsustainabilityandqualityoflife
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SlidecourtesyWolframMauser
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D.Kranzlmüller Cracow,26October2016 29
Environmental (Friendly) Supercomputingon SuperMUC
Dieter Kranzlmüllerkranzlmueller@lrz.de
Photo:Karl Behler
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